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Digitization principles or digitization strategy? 

Whatever von Clausewitz thought, the concept of strategy is interpreted and applied very differently in business management theory and corporate practice. Nevertheless, there seems to be general agreement that our strategy defines rules on how to achieve the medium- and long-term goals derived from the company's purpose.

The strategic plan and the tasks and measures derived from it define the steps in which the strategy is to be implemented, typically over a period of three to five years.

On the one hand, Digitization is a means to an end, but on the other hand an enabler for the strategy. In other words, digitalization can help to achieve given goals more efficiently and effectively. But it also creates options for more or less disruptive business systems.


Figure 1

In our opinion, digitization does not require a strategy of its own; rather, the complete integration of digitization activities into an overarching corporate strategy is the key success factor. Above all, this prevents digitization from happening just for the sake of digitization, leading to an unsatisfactory ‘return on digitization’ from the company's point of view. In addition, lack of integration brings with it the risk of parallel universes with different values, rules and goals, dividing a company into two camps, suspiciously eyeing each other up from a distance. This may be intentional, but it does not have to be, especially since there are excellent examples of successful integration.

Establishing a set of principles is one way to a link corporate strategy and digitization activities. Such principles set out what to look out for during digitization to ensure it delivers optimal value for the entire organization, but without being too prescriptive or restricting room for strategic initiatives driven by digitization.

We would like to outline a set of ten digitization principles which as a package aim to maximize the return on digitization.

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Figure 2

The principles have no order and, depending on the company and corporate strategy, different weightings. However, it is certainly worthwhile to think about each of these principles in turn.


This is based on the principle that customers measure the value of products or services by how well they help them perform their tasks or achieve their objectives. It may be the case that the customer knows exactly what helps to best to achieve their goals, but not necessarily. Henry Ford allegedly expressed this vividly - long before digitisation: "If I had asked people what they wanted, they would have said faster horses.”

The statement cannot easily be transferred to the present. But even if Ford’s idea of understanding customer needs is not new, the numerous and effective ways companies now use to identify true customer needs, certainly are. Our smartphone therefore probably knows more about us and what we might need tomorrow than we do ourselves. And all because it accompanies us every day, collects data, recognizes statistically significant patterns and at least has the potential to predict our reactions to changes, such as price fluctuations or weather changes.


The greater the benefits for those involved and affected, the more successful digitisation is. Of course, this does not have to be about convenience, but since digitisation replaces manual activities in many cases, it makes sense to turn this into added value for those involved and affected. The desire for reduced stress is also widespread, not least due to years of various cost-cutting programs, which has often led to additional workload, particularly for high performers.

A better workflow, fewer clicks, fewer potential errors, automation of tedious standard tasks - all are examples of how digitization can create convenience for employees and customers alike. Convenience is often rewarded, even at the cost of data protection. We are now fully accustomed to cookies, the same goes for location recognition on our smartphones and automatic data and password entry is no longer a big issue for a lot of users. 

However, we should bear in mind that digitization can also lead to additional effort – the new rules for safer cyber-payments are a good example of this. We therefore need to ensure that digitalization makes life easier, as this will significantly increase acceptance!


Despite increasing sensitivity to data privacy, our willingness to disclose personal information is still very high… at least if we stand to benefit from it. To name a couple of examples, this benefit could be increased ease of use, speed or simply the ability to access certain services.

Of course, there’s no such thing as a free lunch, and these benefits are paid for with our data. The beauty, however, is that our personal data can be used as a means of payment - in principle as often as we want. 

Our theory is: If a benefit is visible, people are willing to pay - if necessary in the form of data. Conversely, for companies this means that if they want to harvest data, they must offer some form of added value – which is clearly recognizable to the customer.


This principle is very similar to the previous one. But with one major difference that may have evolved historically: companies often don’t use data they have available to them, even if it is self-generated, for example from production. So non-use of data isn’t always due to GDPR! 

Often we simply do not know which data is generated by processes and systems, and how it can be interpreted and utilized. This doesn't have to be the case. Process Mining and Business Intelligence tools are becoming increasingly important as processes become more and more digitized. The number of data points increases with automation and, above all, via the interconnection of different systems. This can be smartphones used for monitoring or as controllers, or sensors collecting data at various points in a process.

In addition to data availability, there is one major reason why businesses don’t benefit more from data, that itself has nothing to do with digitisation at all: at the end we have to make relevant information out of this data, which in turn has to be translated into actions - or at least recommendations for actions. In addition to a knowledge of descriptive and inductive statistics, this requires a healthy understanding of business and processes. This is easier said than done, as statistics is a field in which specialists often speak a completely different language than managers. This is where we need translators, intermediaries between the two worlds. 

Lastly, we should bear in mind that data must be good data – leading us to our next digitization principle:


The statement that a lot of data is always better than a small amount of data in order to do statistical analysis, is unfortunately not always correct. Statistics tells us how large our data sample must be to draw representative conclusions about the reality we are testing, depending on our data quality. So far, so good. The caveat "depending on our data quality" is highly important and should be fairly intuitive and easy to understand. However, all too often issues with the data quality are the fly in the ointment, but are lost in the communication. If this leads to wrong decisions, it can have very expensive consequences.

So what makes good quality data? Numerous articles and books have been written on this subject, and it would go beyond the scope of our article to go deeper here. We would therefore offer the following guideline1 which in our opinion is very helpful for orientation purposes1:

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Table 1

Since the definition of these quality criteria alone is not enough, the fulfilment of the criteria must be managed. 


This principle should ensure that digitisation is not seen and managed as an end in itself, but as a means to an end. We covered considerations on this matter at the beginning of the article.


The seventh principle is closely linked to the sixth and is based on the hypothesis that digitisation ultimately will be relevant to and affect everyone in one way or another. Be it in one’s professional or private life, actively or passively. When digitization finds its way into a company or its use further intensified, the acceptance of digitization by employees is a critical factor for success. Knowledge of digitisation should act as a catalyst to its acceptance, even if only because knowledge increases understanding and helps remove unfounded fears.

However, in some situations it may be wise to temporarily ignore this strategy, for example when the goal is to build up digitisation knowledge and gain experience in the shortest possible time. Many companies now set up independent legal entities to attract digitisation experts, offering an attractive start-up vibe and space for experiments. After the initial euphoria, however, the question arises how the core organization can benefit from the knowledge and skills of this “garage” unit in the long term. It is also important to make constructive use of the internal friction or competition between the core and garage organizations, which is often unavoidable or may even be intended. Two major challenges – which in some companies remain unsolved – should not be underestimated here: The efficient and effective transfer of know-how, and the constructive cooperation between old and new organizational units. Our recommendation: Right from the start, prepare the way for reintegration of such garage units later. Their reintegration is a deciding factor in achieving a positive return on digitization.


What is the use of a digital process if it is not used? Benefit comes from utilization, and utilization requires not only skill but also the will and the freedom or empowerment to use. These factors are not specific to digitization, they are prerequisites for any successful change. The user must recognize the value and meaning of the change, which does not necessarily mean for themselves. If someone uses a new tool for a job, they must learn the skills to use it. This learning is often accompanied by initial mistakes or a temporary loss of performance. Pressure and high expectations from management that the introduction of a digital process, for example, will have immediate positive results, is usually counterproductive and unrealistic. Achieving visible and measurable improvements simply takes time that cannot be shortened at will. In other words, if you want to see early results, you should start the change process early.

One positive side-effect: People who are involved in problem analysis, solution development and implementation planning from an early stage can bring in their knowledge and experience and usually contribute to better results.


The essence of digitisation is, among other things, the speed at which technology, user behaviour and user requirements change. The consequence of – and also the answer to – this speed of change is shorter product life cycles and development cycles. This in turn requires a new approach to innovation. Instead of long and painstaking research and development work, the courage to try out new concepts and prototypes as early as possible is becoming increasingly necessary. The idea behind this is that failing fast leads to rapid learning and adaptation. Traditional waterfall planning and business cases that only provide for a return on investment after five years or more, are often no longer an option.

What is particularly important within these short test and learning cycles, is to listen to potential customers, be open to their opinions and alternative solutions, and to impartially observe their behavior. The aim is not to confirm our own opinions, but rather to gain new insights. This in turn requires the willingness to get to know the customer’s own processes better, to recognize their true needs and, if necessary, to part with our own solutions. Which brings us back to the first digitization principle. And the earlier we test our ideas and the cheaper the prototype, the easier this is to do.


The final digitization principle is the answer to an observation we see time and time again: Agility is often confused with volatility. What is the main difference? Volatility is a measure of instability. Agile behavior, on the other hand, should help us to reach a given goal in an unstable environment. A key characteristic of agility is the ability to react quickly to change without losing sight of the original goal. Agility is an organizational capability that is not based on willpower alone. In addition to goals that are set free of solutions at the start, it requires skill and empowerment. The willingness and courage of management or employees to act in an agile way is of central importance, but appropriate individual skills, values and paradigms as well as processes and structures to support agile behavior are also required. 

That concludes the overview of the ten principles of digitisation. Their key advantage is that - similarly to our Excellence Principles - they show patterns that can be incorporated not just in the design of digitization activities, but also in the continued improvement of existing ones.

1Vgl. HUANG et al., Quality Information and Knowledge, Prentice Hall, Upper Saddle River, NJ 1999, S. 43.